As used herein, the term skew refers to a rotational misalignment of an image, such as an image of a document, with respect to a coordinate system, such as the coordinate system of a scanner used to capture an image of the document. Character recognition or other classification algorithms often depend on a minimally acceptable alignment of the scanned document being analyzed. Skew not only affects processes such as character recognition, but also degrades the quality of document display.
A variety of techniques are typically employed to ensure proper alignment with respect to a scanner's (or similar imaging device) imaging coordinate system. Such techniques may include the use of automatic document feeders, guides, arms, etc., to physically align a scanned document as it is fed into the scanner. However, these techniques can be costly, can reduce document throughput, and may frequently be unreliable. For example, the document may not be fed properly into the scanner due to tears, wrinkles, or a feed mechanism malfunction. In addition, many scanners permit manual positioning of bulky items such as books. The resulting scanned images will frequently be skewed, thereby prohibiting or at least inhibiting successful classification processes such as character recognition.
Automatic methods of skew detection may also be employed. However, textures, lines, images, characters, or some mixture thereof on a document's face and/or the occasional presence of tears and wrinkles pose significant challenges for quick and accurate skew detection.
It would be desirable if a scanned document could be de-skewed with a simple and effective process that does not depend on mechanical means.